UX benchmarking allows us to track the long-term changes in the overall user experience of our product, while UX success metrics help us assess the short-term impact of a specific project or feature launch.
Likert scales measure user opinions by asking participants to rate statements. They capture nuanced feedback but can face biases. To improve accuracy, use clear questions and techniques to reduce bias.
Discover how custom events in analytics can transform your UX strategy by providing detailed insights into critical user behaviors, allowing for better-informed design decisions.
Competitive usability evaluations help you understand how your competitors solve certain design problems and how you might outperform them. These evaluations are often performed at the beginning of design projects to shift their direction toward areas of opportunity.
Statistical significance does not always equal practical significance. A difference may be statistically significant without having any meaningful impact in real life. Conversely, practical differences may not always achieve statistical significance.
Measure your intranet's effectiveness with strategic metrics for usage patterns, employee engagement, and satisfaction ratings. Improve your organization through insightful intranet analysis.
Measure completion rate when users follow a linear process with a fixed number of steps; use success rate when there are multiple ways to accomplish a task.
Presenting study data to stakeholders is a crucial step of most projects. Make sure to present your data truthfully and responsibly to avoid costly negative outcomes and reputation loss. Indicate who your data represents and communicate the limitations of your findings.
Measurement error is the error we introduce when we measure or observe something about our users. It can come from different sources, such as the number of participants, individual variation between participants, testing environment, or other outside factors. This video helps understand and communicate such measurement errors.
The product-led growth model enables users to try a product or service before paying. This video offers three tips for UX professionals to support a product-led user experience: Connect changes to metrics, interview/survey users, and compare behavior and feedback.
False positives and negatives are common errors in quantitative studies that can lead to harmful business decisions. To avoid these mistakes recruit large enough sample sizes, representative participants, and control for confounding variables.
Avoid creating personas from analytics data alone. Personas are artifacts that aim to capture users' attitudes, goals, and pain points, aspects which analytics alone can't provide.
Engagement is an abstract, complex concept used to understand how much people interact with our products. Choosing the right engagement metrics goes beyond time spent.
